Answer Set Programming (ASP) is a powerful declarative programming paradigm commonly used for solving challenging search and optimization problems. The modeling languages of ASP are supported by sophisticated solving algorithms (solvers) that make the solution search efficient while enabling the programmer to model the problem at a high level of abstraction. As an approach to Knowledge Representation and Reasoning, ASP benefits from its simplicity, conciseness and rigorously defined semantics. These characteristics make ASP a straightforward way to develop formally verifiable programs. In the context of artificial intelligence (AI), the clarity of ASP programs lends itself to the construction of explainable, trustworthy AI. In support of these goals, my research is concerned with extending the theory and tools supporting the verification of ASP progams.
翻译:答案设置编程(ASP)是一个强大的宣示性编程模式,通常用于解决具有挑战性的搜索和优化问题。ASP的模拟语言得到精密的解算法(解算法)的支持,这些算法使解决方案搜索效率高,同时使程序设计者能够以高度抽象的方式模拟问题。作为一种处理知识代表性和理性的方法,ASP得益于其简单、简洁和严格定义的语义。这些特征使ASP成为开发可正式核查程序的一个直截了当的方法。在人工智能(AI)方面,ASP程序的清晰度有助于构建可解释、可信赖的AI。为了支持这些目标,我的研究涉及扩展支持ASP progams核查的理论和工具。